Andrew Shao's repositories
CESM_share
CESM shared code
cime
Common Infrastructure for Modeling the Earth
code
Source code for the General Ocean Turbulence Model
End-to-End-LLM
This repository is an AI Bootcamp material that consist of a workflow for LLM
Forpy_CNN_GZ21
Machine learned parameterization (Guillaumin and Zanna, 2021) implemented in MOM6 with Forpy
FourCastNet
Initial public release of code, data, and model weights for FourCastNet
jupyter-forward
Jupyter Lab Port Forwarding Utility
ml_lib_builder
Build ML backends for Mac OSX
modulus
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
MOM6-smartredis
Contains SmartRedis integrations into MOM6 for various machine learning and visualization tasks
NCAR_ML_EKE
Repository for paper -- Using Machine Learning at Scale in HPC Simulations with SmartSim: An Application to Ocean Climate Modeling
NEMO-examples
Simple configurations to study specific oceanic physical processes and be used as a tool for training
Newton-Krylov_OOC
An Out-of-Core Newton-Krylov Solver
OFMLHackathon
OpenFOAM and Machine Learning Hackathon
OpenFOAM-Multi-Objective-Optimization
A tiny project to use ax-platform for multi-objective optimization on OpenFOAM cases
openfoam-smartsim
Sub-module for OpenFOAM that provides a solver for embedding SmartSim and its external dependencies (i.e. SmartRedis) into OpenFOAM.
Phase-space-sampling
Reduce a large and high-dimensional dataset by downselecting data uniformly in phase space
redis-plus-plus
Redis client written in C++
RedisAI
A Redis module for serving tensors and executing deep learning graphs
sgs_model_test_transient
Evaluation of an SGS model for mass transfer at risining bubbles in the initial transient stage
SmartRedis
SmartSim Infrastructure Library Clients.
SmartSim
SmartSim Infrastructure Library.
SmartSim-Scaling
A repository of SmartSim scaling data and information
SmartSim-Zoo
A repository of CrayLabs and user contributed examples of using SmartSim.